Performance assessment of selected wireless sensors for biomass smoke air quality monitoring | |
| Author | Huynh Tan Loi |
| Call Number | AIT Thesis no.EV-16-07 |
| Subject(s) | Sensor networks. Air quality Air pollution |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Environmental Engineering and Management |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis ; no. EV-16-07 |
| Abstract | Air pollutant concentrations fluctuate with location and time hence it is challenging to capture these changes and timely disseminate air quality information to public. The traditional monitoring methods use equipment to take samples for subsequent analyses or to measure online air quality which are widely used. However this traditional monitoring takes considerable resources for sampling, analyzing and publicizing the information. Wireless sensing, a new technology for air pollution monitoring can help solve these problems. This study assessed the applicability of wireless sensors for monitoring of PM –Sharp GP2Y1010, for CO –MQ9 and for CO₂–MG811 in biomass smoke pollution. Arduino platform was used as a microcontroller and data transmitter which uploaded the sensor signals via 3G network to Thing-speak, an Internet open source for publicizing. Two identical sensors nodes were developed each consisted 1 sensor for CO, 1 sensor for PM (PM10 and PM2.5) and 1 CO₂ sensor. The sensors were first calibrated by collocating with standard equipment for two ranges of air pollutant concentrations: (1) ambient air concentrations (CO: 0 –6.8 ppm; PM10: 33 –76 μg/m³; PM2.5: 18 –50 μg/m³) measured at PCD automatic air quality monitoring stations in Bangkok, and (2) high concentrations in crop field burning smoke. The results showed that sensors worked better at high concentration levels in the smoke (CO: 18 –132 ppm, PM10: 233 –966 μg/m³; PM2.5: 195 –879 μg/m³). The relationships between sensors signals and PCD data showed good linearity with the coefficients of determination (R2) of 0.92 for PM2.5, 0.91 for PM10 and 0.91 for CO. At the low levels found in the ambient air, only moderate linearity was found with R2of 0.50 for PM2.5, 0.91 for PM10and 0.71 for CO. The calibrated sensors were used in a trial monitoring for crop burning haze in Chiang Rai, Thailand. There was not enough monitoring data from the standard equipment for calibration of CO₂ sensor hence was not included in the trial monitoring. The results of haze monitoring in Chiang Rai showed that the sensors can response well to the levels of pollution in the smoke plume and showed higher levels (24-hour PM10: 150 -225 μg/m³, 24-hour PM2.5: 125 –189 μg/m³; 8-hour CO 2.7 –7.1 ppm) at one site that hit by the smoke plume and lower level (24-hour PM10: 91–97 μg/m³, 24-hour PM2.5: 46 –55 μg/m³; 8-hour CO 0.8 –1.6 ppm) at another site which was not hit by smoke plume. The ratio of PM2.5/PM10 at site that hit by the smoke plume was significantly higher (0.84), indicating the effects of biomass burning, at the smoke hit site. This study thus showed that wireless sensing is promising technology in air pollution monitoring especially for the biomass burning smoke such as crop or forest fires. The problems encountered by monitoring of low ambient levels of pollutants should be addressed by using sensors with higher sensitivity. The sensors were relatively low cost and small size hence a network with many sensors can be used. The monitoring results can be easily publicized through internet access and the database could be handled by cloud computing. Other sensors such as those for black carbon and volatile organic compounds should also be used for biomass smoke monitoring. |
| Year | 2016 |
| Type | Thesis |
| School | School of Environment, Resources, and Development (SERD) |
| Department | Department of Energy and Climate Change (Former title: Department of Energy, Environment, and Climate Change (DEECC)) |
| Academic Program/FoS | Environmental Engineering and Management (EV) |
| Chairperson(s) | Nguyen, Thi Kim Oanh; |
| Examination Committee(s) | Kanchana Kanchanasut;Visvanathan, C.; |
| Scholarship Donor(s) | Greater Mekong Sub Region (GMS) Scholarship; |
| Degree | Thesis (M.Eng.) - Asian Institute of Technology, 2016 |